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/*! \file
    \brief Tests for device-wide Implicit GEMM interface
*/

#include "../../common/cutlass_unit_test.h"
#include "cutlass/cutlass.h"

#include "cutlass/conv/kernel/default_conv2d_dgrad.h"
#include "cutlass/conv/device/implicit_gemm_convolution.h"

#include "conv2d_testbed.h"

#if defined(CUTLASS_ARCH_MMA_SM80_SUPPORTED)

////////////////////////////////////////////////////////////////////////////////
TEST(SM80_Device_Conv2d_Dgrad_Analytic_ImplicitGemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16,
     128x128_64x3_64x64x64) {
    /// Conv operation element types for the Gemm equivalent (ImplicitGemm)
    using ElementA = cutlass::half_t;
    using ElementB = cutlass::half_t;
    using ElementC = cutlass::half_t;
    using ElementAccumulator = cutlass::half_t;
    using ElementCompute = cutlass::half_t;

    /// Device-level Conv2d instance
    using Conv2dDgradKernel =
            typename cutlass::conv::kernel::DefaultConv2dDgrad<
                    ElementA, cutlass::layout::TensorNHWC, ElementB,
                    cutlass::layout::TensorNHWC, ElementC,
                    cutlass::layout::TensorNHWC, ElementAccumulator,
                    cutlass::arch::OpClassTensorOp, cutlass::arch::Sm80,
                    cutlass::gemm::GemmShape<128, 128, 64>,
                    cutlass::gemm::GemmShape<64, 64, 64>,
                    cutlass::gemm::GemmShape<16, 8, 16>,
                    cutlass::epilogue::thread::LinearCombination<
                            ElementC,
                            128 / cutlass::sizeof_bits<ElementC>::value,
                            ElementAccumulator, ElementCompute>,
                    cutlass::gemm::threadblock::
                            GemmIdentityThreadblockSwizzle<>,
                    3, cutlass::arch::OpMultiplyAdd,
                    cutlass::conv::IteratorAlgorithm::kAnalytic>::Kernel;

    using Conv2dDgrad =
            cutlass::conv::device::ImplicitGemmConvolution<Conv2dDgradKernel>;

    /// Run all unit test sizes with device-level Conv2d instance
    EXPECT_TRUE(test::conv::device::TestAllConv2d<Conv2dDgrad>());
}

////////////////////////////////////////////////////////////////////////////////
TEST(SM80_Device_Conv2d_Dgrad_Optimized_ImplicitGemm_f16nhwc_f16nhwc_f16nhwc_tensor_op_f16,
     128x128_64x3_64x64x64) {
    /// Conv operation element types for the Gemm equivalent (ImplicitGemm)
    using ElementA = cutlass::half_t;
    using ElementB = cutlass::half_t;
    using ElementC = cutlass::half_t;
    using ElementAccumulator = cutlass::half_t;
    using ElementCompute = cutlass::half_t;

    /// Device-level Conv2d instance
    using Conv2dDgradKernel =
            typename cutlass::conv::kernel::DefaultConv2dDgrad<
                    ElementA, cutlass::layout::TensorNHWC, ElementB,
                    cutlass::layout::TensorNHWC, ElementC,
                    cutlass::layout::TensorNHWC, ElementAccumulator,
                    cutlass::arch::OpClassTensorOp, cutlass::arch::Sm80,
                    cutlass::gemm::GemmShape<128, 128, 64>,
                    cutlass::gemm::GemmShape<64, 64, 64>,
                    cutlass::gemm::GemmShape<16, 8, 16>,
                    cutlass::epilogue::thread::LinearCombination<
                            ElementC,
                            128 / cutlass::sizeof_bits<ElementC>::value,
                            ElementAccumulator, ElementCompute>,
                    cutlass::gemm::threadblock::
                            GemmIdentityThreadblockSwizzle<>,
                    3, cutlass::arch::OpMultiplyAdd,
                    cutlass::conv::IteratorAlgorithm::kOptimized,
                    cutlass::conv::StrideSupport::kUnity>::Kernel;

    using Conv2dDgrad =
            cutlass::conv::device::ImplicitGemmConvolution<Conv2dDgradKernel>;

    /// Run all unit test sizes with device-level Conv2d instance
    EXPECT_TRUE(test::conv::device::TestAllConv2d<Conv2dDgrad>());
}

////////////////////////////////////////////////////////////////////////////////
#endif  // CUTLASS_ARCH_MMA_SM80_SUPPORTED
